--- layout: documentation title: Malloy Documentation footer: /generated/footers/examples/iowa/step6.html ---
Putting it all together we can write a dashboard
query: vendor_dashboard is { group_by: vendor_count is count(distinct vendor_number) aggregate: total_sale_dollars total_bottles nest: by_month by_class by_vendor_bar_chart top_sellers_by_revenue most_expensive_products by_vendor_dashboard is { top: 10 group_by: vendor_name aggregate: total_sale_dollars nest: by_month, top_sellers_by_revenue, most_expensive_products } }
Simply add some filters. Notice the sub-dashboard for each of the Vendors.
query: iowa { where: category_class = 'VODKAS' } -> vendor_dashboard[ { "vendor_count": 262, "total_sale_dollars": 769629916.9500663, "total_bottles": 71758747, "by_month": [ { "purchase_month": { "value": "2012-01-01" }, "total_sale_dollars": 610057.1599999997 }, { "purchase_month": { "value": "2012-01-08" }, "total_sale_dollars": 802949.41 }, { "purchase_month": { "value": "2012-01-15" }, "total_sale_dollars": 935417.8 }, { "purchase_month": { "value": "2012-01-22" }, "total_sale_dollars": 988698.7400000001 }, { "purchase_month": { "value": "2012-01-29" }, "total_sale_dollars": 938111.7300000001 }, { "purchase_month": { "value": "2012-02-05" }, "total_sale_dollars": 902035.6900000004 }, { "purchase_month": { "value": "2012-02-12" }, "total_sale_dollars": 896318.04 }, { "purchase_month": { "value": "2012-02-19" }, "total_sale_dollars": 980946.7700000007 }, { "purchase_month": { "value": "2012-02-26" }, "total_sale_dollars": 893080.9900000001 }, { "purchase_month": { "value": "2012-03-04" }, "total_sale_dollars": 976248.3900000004 }, { "purchase_month": { "value": "2012-03-11" }, "total_sale_dollars": 1018939.0200000004 }, { "purchase_month": { "value": "2012-03-18" }, "total_sale_dollars": 1007704.9700000006 }, { "purchase_month": { "value": "2012-03-25" }, "total_sale_dollars": 955948.0500000003 }, { "purchase_month": { "value": "2012-04-01" }, "total_sale_dollars": 1152349.6600000004 }, { "purchase_month": { "value": "2012-04-08" }, "total_sale_dollars": 1139967.6000000003 }, { "purchase_month": { "value": "2012-04-15" }, "total_sale_dollars": 1035155.4400000004 }, { "purchase_month": { "value": "2012-04-22" }, "total_sale_dollars": 1067074.1300000004 }, { "purchase_month": { "value": "2012-04-29" }, "total_sale_dollars": 1087894.9100000004 }, { "purchase_month": { "value": "2012-05-06" }, "total_sale_dollars": 1101532.0000000005 }, { "purchase_month": { "value": "2012-05-13" }, "total_sale_dollars": 1096981.29 }, { "purchase_month": { "value": "2012-05-20" }, "total_sale_dollars": 1386355.5899999999 }, { "purchase_month": { "value": "2012-05-27" }, "total_sale_dollars": 863731.4899999999 }, { "purchase_month": { "value": "2012-06-03" }, "total_sale_dollars": 1236165.5900000005 }, { "purchase_month": { "value": "2012-06-10" }, "total_sale_dollars": 1296151.4000000004 }, { "purchase_month": { "value": "2012-06-17" }, "total_sale_dollars": 1182540.5000000002 }, { "purchase_month": { "value": "2012-06-24" }, "total_sale_dollars": 1613062.2999999998 }, { "purchase_month": { "value": "2012-07-01" }, "total_sale_dollars": 1173113.4700000007 }, { "purchase_month": { "value": "2012-07-08" }, "total_sale_dollars": 1132063.4000000004 }, { "purchase_month": { "value": "2012-07-15" }, "total_sale_dollars": 1238239.71 }, { "purchase_month": { "value": "2012-07-22" }, "total_sale_dollars": 1072884.2100000002 }, { "purchase_month": { "value": "2012-07-29" }, "total_sale_dollars": 1214136.06 }, { "purchase_month": { "value": "2012-08-05" }, "total_sale_dollars": 1272308.5300000003 }, { "purchase_month": { "value": "2012-08-12" }, "total_sale_dollars": 1187809.7599999998 }, { "purchase_month": { "value": "2012-08-19" }, "total_sale_dollars": 1141115.1600000001 }, { "purchase_month": { "value": "2012-08-26" }, "total_sale_dollars": 1580034.549999999 }, { "purchase_month": { "value": "2012-09-02" }, "total_sale_dollars": 968773.63 }, { "purchase_month": { "value": "2012-09-09" }, "total_sale_dollars": 1244709.0400000003 }, { "purchase_month": { "value": "2012-09-16" }, "total_sale_dollars": 990731.3400000002 }, { "purchase_month": { "value": "2012-09-23" }, "total_sale_dollars": 995239.1300000002 }, { "purchase_month": { "value": "2012-09-30" }, "total_sale_dollars": 1577376.0799999991 }, { "purchase_month": { "value": "2012-10-07" }, "total_sale_dollars": 1541959.399999999 }, { "purchase_month": { "value": "2012-10-14" }, "total_sale_dollars": 1682916.7899999996 }, { "purchase_month": { "value": "2012-10-21" }, "total_sale_dollars": 1642773.71 }, { "purchase_month": { "value": "2012-10-28" }, "total_sale_dollars": 936511.5500000003 }, { "purchase_month": { "value": "2012-11-04" }, "total_sale_dollars": 965583.9800000003 }, { "purchase_month": { "value": "2012-11-11" }, "total_sale_dollars": 1338893.68 }, { "purchase_month": { "value": "2012-11-18" }, "total_sale_dollars": 417664.56999999983 }, { "purchase_month": { "value": "2012-11-25" }, "total_sale_dollars": 1055019.36 }, { "purchase_month": { "value": "2012-12-02" }, "total_sale_dollars": 975292.2500000005 }, { "purchase_month": { "value": "2012-12-09" }, "total_sale_dollars": 1213524.68 }, { "purchase_month": { "value": "2012-12-16" }, "total_sale_dollars": 1460909.3599999999 }, { "purchase_month": { "value": "2012-12-23" }, "total_sale_dollars": 1150477.76 }, { "purchase_month": { "value": "2012-12-30" }, "total_sale_dollars": 720803.4999999997 }, { "purchase_month": { "value": "2013-01-06" }, "total_sale_dollars": 949135.3799999999 }, { "purchase_month": { "value": "2013-01-13" }, "total_sale_dollars": 957667.99 }, { "purchase_month": { "value": "2013-01-20" }, "total_sale_dollars": 967562.5400000003 }, { "purchase_month": { "value": "2013-01-27" }, "total_sale_dollars": 966908.61 }, { "purchase_month": { "value": "2013-02-03" }, "total_sale_dollars": 975876.4100000006 }, { "purchase_month": { "value": "2013-02-10" }, "total_sale_dollars": 1009914.9500000001 }, { "purchase_month": { "value": "2013-02-17" }, "total_sale_dollars": 911923.5300000004 }, { "purchase_month": { "value": "2013-02-24" }, "total_sale_dollars": 1022277.8000000004 }, { "purchase_month": { "value": "2013-03-03" }, "total_sale_dollars": 992121.5200000005 }, { "purchase_month": { "value": "2013-03-10" }, "total_sale_dollars": 1037159.8800000006 }, { "purchase_month": { "value": "2013-03-17" }, "total_sale_dollars": 977889.1300000004 }, { "purchase_month": { "value": "2013-03-24" }, "total_sale_dollars": 990155.8400000005 }, { "purchase_month": { "value": "2013-03-31" }, "total_sale_dollars": 1253060.6700000002 }, { "purchase_month": { "value": "2013-04-07" }, "total_sale_dollars": 1394217.5800000003 }, { "purchase_month": { "value": "2013-04-14" }, "total_sale_dollars": 1065129.9800000007 }, { "purchase_month": { "value": "2013-04-21" }, "total_sale_dollars": 1096815.3400000005 }, { "purchase_month": { "value": "2013-04-28" }, "total_sale_dollars": 1128926.2100000007 }, { "purchase_month": { "value": "2013-05-05" }, "total_sale_dollars": 1208798.7300000004 }, { "purchase_month": { "value": "2013-05-12" }, "total_sale_dollars": 1087199.6000000006 }, { "purchase_month": { "value": "2013-05-19" }, "total_sale_dollars": 1303872.660000001 }, { "purchase_month": { "value": "2013-05-26" }, "total_sale_dollars": 1352285.6500000004 }, { "purchase_month": { "value": "2013-06-02" }, "total_sale_dollars": 1175720.1400000008 }, { "purchase_month": { "value": "2013-06-09" }, "total_sale_dollars": 1712168.53 }, { "purchase_month": { "value": "2013-06-16" }, "total_sale_dollars": 545374.73 }, { "purchase_month": { "value": "2013-06-23" }, "total_sale_dollars": 1576071.4400000006 }, { "purchase_month": { "value": "2013-06-30" }, "total_sale_dollars": 1169665.5600000008 }, { "purchase_month": { "value": "2013-07-07" }, "total_sale_dollars": 1239827.1000000006 }, { "purchase_month": { "value": "2013-07-14" }, "total_sale_dollars": 1153773.000000001 }, { "purchase_month": { "value": "2013-07-21" }, "total_sale_dollars": 1142628.430000001 }, { "purchase_month": { "value": "2013-07-28" }, "total_sale_dollars": 1254123.7000000007 }, { "purchase_month": { "value": "2013-08-04" }, "total_sale_dollars": 1315882.1600000004 }, { "purchase_month": { "value": "2013-08-11" }, "total_sale_dollars": 1371907.6700000004 }, { "purchase_month": { "value": "2013-08-18" }, "total_sale_dollars": 1191809.2600000005 }, { "purchase_month": { "value": "2013-08-25" }, "total_sale_dollars": 1402540.7100000002 }, { "purchase_month": { "value": 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38048 }, { "purchase_month": { "value": "2022-02-27" }, "total_sale_dollars": 35268.63999999999 }, { "purchase_month": { "value": "2022-03-06" }, "total_sale_dollars": 36031.16 }, { "purchase_month": { "value": "2022-03-13" }, "total_sale_dollars": 30312.959999999995 }, { "purchase_month": { "value": "2022-03-20" }, "total_sale_dollars": 36157.320000000014 }, { "purchase_month": { "value": "2022-03-27" }, "total_sale_dollars": 26304.160000000003 } ], "top_sellers_by_revenue": [ { "vendor_name": "Laird And Company", "item_description": "Five O'clock Vodka", "total_sale_dollars": 19427509.879999004, "total_bottles": 3261856, "avg_price_per_100ml": 0.6656423906070659 }, { "vendor_name": "Laird And Company", "item_description": "Five O'Clock Vodka", "total_sale_dollars": 5233183.240000074, "total_bottles": 891634, "avg_price_per_100ml": 0.6693155975786335 }, { "vendor_name": "Laird And Company", "item_description": "Five O'clock PET Vodka", "total_sale_dollars": 2772248.5200000242, "total_bottles": 548134, "avg_price_per_100ml": 0.6731975639792838 }, { "vendor_name": "Laird And Company", "item_description": "Five O'Clock Vodka PET", "total_sale_dollars": 839362.9200000003, "total_bottles": 165882, "avg_price_per_100ml": 0.6746666666666666 } ], "most_expensive_products": [ { "vendor_name": "Laird And Company", "item_description": "Five O'Clock Vodka PET", "total_sale_dollars": 839362.9200000004, "total_bottles": 165882, "avg_price_per_100ml": 0.6746666666666666 }, { "vendor_name": "Laird And Company", "item_description": "Five O'clock PET Vodka", "total_sale_dollars": 2772248.5200000233, "total_bottles": 548134, "avg_price_per_100ml": 0.6731975639792838 }, { "vendor_name": "Laird And Company", "item_description": "Five O'Clock Vodka", "total_sale_dollars": 5233183.240000075, "total_bottles": 891634, "avg_price_per_100ml": 0.6693155975786336 }, { "vendor_name": "Laird And Company", "item_description": "Five O'clock Vodka", "total_sale_dollars": 19427509.879999, "total_bottles": 3261856, "avg_price_per_100ml": 0.6656423906070659 } ] } ] } ]
WITH __stage0 AS ( SELECT group_set, CASE WHEN group_set=0 THEN count(distinct iowa.vendor_number) END as vendor_count__0, CASE WHEN group_set=0 THEN SUM(iowa.sale_dollars) END as total_sale_dollars__0, CASE WHEN group_set=0 THEN SUM(iowa.bottles_sold) END as total_bottles__0, CASE WHEN group_set=1 THEN DATE_TRUNC(iowa.date, WEEK) END as purchase_month__1, CASE WHEN group_set=1 THEN SUM(iowa.sale_dollars) END as total_sale_dollars__1, CASE WHEN group_set=2 THEN CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END END as category_class__2, CASE WHEN group_set=2 THEN SUM(iowa.sale_dollars) END as total_sale_dollars__2, CASE WHEN group_set=2 THEN count(distinct iowa.item_number) END as item_count__2, CASE WHEN group_set=3 THEN iowa.vendor_name END as vendor_name__3, CASE WHEN group_set=3 THEN SUM(iowa.sale_dollars) END as total_sale_dollars__3, CASE WHEN group_set=3 THEN SUM(iowa.bottles_sold) END as total_bottles__3, CASE WHEN group_set=4 THEN iowa.vendor_name END as vendor_name__4, CASE WHEN group_set=4 THEN iowa.item_description END as item_description__4, CASE WHEN group_set=4 THEN SUM(iowa.sale_dollars) END as total_sale_dollars__4, CASE WHEN group_set=4 THEN SUM(iowa.bottles_sold) END as total_bottles__4, CASE WHEN group_set=4 THEN AVG(((iowa.state_bottle_retail/(nullif(iowa.bottle_volume_ml,0)))*100)) END as avg_price_per_100ml__4, CASE WHEN group_set=5 THEN iowa.vendor_name END as vendor_name__5, CASE WHEN group_set=5 THEN iowa.item_description END as item_description__5, CASE WHEN group_set=5 THEN SUM(iowa.sale_dollars) END as total_sale_dollars__5, CASE WHEN group_set=5 THEN SUM(iowa.bottles_sold) END as total_bottles__5, CASE WHEN group_set=5 THEN AVG(((iowa.state_bottle_retail/(nullif(iowa.bottle_volume_ml,0)))*100)) END as avg_price_per_100ml__5, CASE WHEN group_set IN (6,7,8,9) THEN iowa.vendor_name END as vendor_name__6, CASE WHEN group_set=6 THEN SUM(iowa.sale_dollars) END as total_sale_dollars__6, CASE WHEN group_set=7 THEN DATE_TRUNC(iowa.date, WEEK) END as purchase_month__7, CASE WHEN group_set=7 THEN SUM(iowa.sale_dollars) END as total_sale_dollars__7, CASE WHEN group_set=8 THEN iowa.vendor_name END as vendor_name__8, CASE WHEN group_set=8 THEN iowa.item_description END as item_description__8, CASE WHEN group_set=8 THEN SUM(iowa.sale_dollars) END as total_sale_dollars__8, CASE WHEN group_set=8 THEN SUM(iowa.bottles_sold) END as total_bottles__8, CASE WHEN group_set=8 THEN AVG(((iowa.state_bottle_retail/(nullif(iowa.bottle_volume_ml,0)))*100)) END as avg_price_per_100ml__8, CASE WHEN group_set=9 THEN iowa.vendor_name END as vendor_name__9, CASE WHEN group_set=9 THEN iowa.item_description END as item_description__9, CASE WHEN group_set=9 THEN SUM(iowa.sale_dollars) END as total_sale_dollars__9, CASE WHEN group_set=9 THEN SUM(iowa.bottles_sold) END as total_bottles__9, CASE WHEN group_set=9 THEN AVG(((iowa.state_bottle_retail/(nullif(iowa.bottle_volume_ml,0)))*100)) END as avg_price_per_100ml__9 FROM `malloy-data.iowa_liquor_sales.sales_deduped` as iowa CROSS JOIN (SELECT row_number() OVER() -1 group_set FROM UNNEST(GENERATE_ARRAY(0,9,1))) WHERE ((CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END)='VODKAS') AND ((CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END)='VODKAS') AND ((group_set NOT IN (1) OR (group_set IN (1) AND (CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END)='VODKAS'))) AND ((group_set NOT IN (2) OR (group_set IN (2) AND (CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END)='VODKAS'))) AND ((group_set NOT IN (3) OR (group_set IN (3) AND (CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END)='VODKAS'))) AND ((group_set NOT IN (4) OR (group_set IN (4) AND (CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END)='VODKAS'))) AND ((group_set NOT IN (5) OR (group_set IN (5) AND (CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END)='VODKAS'))) AND ((group_set NOT IN (7) OR (group_set IN (7) AND (CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END)='VODKAS'))) AND ((group_set NOT IN (8) OR (group_set IN (8) AND (CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END)='VODKAS'))) AND ((group_set NOT IN (9) OR (group_set IN (9) AND (CASE WHEN REGEXP_CONTAINS(iowa.category_name,r'(WHISK|SCOTCH|BOURBON|RYE)') THEN 'WHISKIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'VODKA') THEN 'VODKAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'RUM') THEN 'RUMS' WHEN REGEXP_CONTAINS(iowa.category_name,r'TEQUILA') THEN 'TEQUILAS' WHEN REGEXP_CONTAINS(iowa.category_name,r'(LIQUE|AMARETTO|TRIPLE SEC)') THEN 'LIQUEURS' WHEN REGEXP_CONTAINS(iowa.category_name,r'BRAND(I|Y)') THEN 'BRANDIES' WHEN REGEXP_CONTAINS(iowa.category_name,r'GIN') THEN 'GINS' WHEN REGEXP_CONTAINS(iowa.category_name,r'SCHNAP') THEN 'SCHNAPPS' ELSE 'OTHER' END)='VODKAS'))) GROUP BY 1,5,7,10,13,14,18,19,23,25,27,28,32,33 ) , __stage1 AS ( SELECT CASE WHEN group_set=7 THEN 6 WHEN group_set=8 THEN 6 WHEN group_set=9 THEN 6 ELSE group_set END as group_set, ANY_VALUE(CASE WHEN group_set=0 THEN vendor_count__0 END) as vendor_count__0, ANY_VALUE(CASE WHEN group_set=0 THEN total_sale_dollars__0 END) as total_sale_dollars__0, ANY_VALUE(CASE WHEN group_set=0 THEN total_bottles__0 END) as total_bottles__0, CASE WHEN group_set=1 THEN purchase_month__1 END as purchase_month__1, ANY_VALUE(CASE WHEN group_set=1 THEN total_sale_dollars__1 END) as total_sale_dollars__1, CASE WHEN group_set=2 THEN category_class__2 END as category_class__2, ANY_VALUE(CASE WHEN group_set=2 THEN total_sale_dollars__2 END) as total_sale_dollars__2, ANY_VALUE(CASE WHEN group_set=2 THEN item_count__2 END) as item_count__2, CASE WHEN group_set=3 THEN vendor_name__3 END as vendor_name__3, ANY_VALUE(CASE WHEN group_set=3 THEN total_sale_dollars__3 END) as total_sale_dollars__3, ANY_VALUE(CASE WHEN group_set=3 THEN total_bottles__3 END) as total_bottles__3, CASE WHEN group_set=4 THEN vendor_name__4 END as vendor_name__4, CASE WHEN group_set=4 THEN item_description__4 END as item_description__4, ANY_VALUE(CASE WHEN group_set=4 THEN total_sale_dollars__4 END) as total_sale_dollars__4, ANY_VALUE(CASE WHEN group_set=4 THEN total_bottles__4 END) as total_bottles__4, ANY_VALUE(CASE WHEN group_set=4 THEN avg_price_per_100ml__4 END) as avg_price_per_100ml__4, CASE WHEN group_set=5 THEN vendor_name__5 END as vendor_name__5, CASE WHEN group_set=5 THEN item_description__5 END as item_description__5, ANY_VALUE(CASE WHEN group_set=5 THEN total_sale_dollars__5 END) as total_sale_dollars__5, ANY_VALUE(CASE WHEN group_set=5 THEN total_bottles__5 END) as total_bottles__5, ANY_VALUE(CASE WHEN group_set=5 THEN avg_price_per_100ml__5 END) as avg_price_per_100ml__5, CASE WHEN group_set IN (6,7,8,9) THEN vendor_name__6 END as vendor_name__6, ANY_VALUE(CASE WHEN group_set=6 THEN total_sale_dollars__6 END) as total_sale_dollars__6, ARRAY_AGG(CASE WHEN group_set=7 THEN STRUCT( purchase_month__7 as purchase_month, total_sale_dollars__7 as total_sale_dollars ) END IGNORE NULLS ORDER BY purchase_month__7 ASC ) as by_month__6, ARRAY_AGG(CASE WHEN group_set=8 THEN STRUCT( vendor_name__8 as vendor_name, item_description__8 as item_description, total_sale_dollars__8 as total_sale_dollars, total_bottles__8 as total_bottles, avg_price_per_100ml__8 as avg_price_per_100ml ) END IGNORE NULLS ORDER BY total_sale_dollars__8 desc LIMIT 5) as top_sellers_by_revenue__6, ARRAY_AGG(CASE WHEN group_set=9 THEN STRUCT( vendor_name__9 as vendor_name, item_description__9 as item_description, total_sale_dollars__9 as total_sale_dollars, total_bottles__9 as total_bottles, avg_price_per_100ml__9 as avg_price_per_100ml ) END IGNORE NULLS ORDER BY avg_price_per_100ml__9 desc LIMIT 10) as most_expensive_products__6 FROM __stage0 GROUP BY 1,5,7,10,13,14,18,19,23 ) SELECT ANY_VALUE(CASE WHEN group_set=0 THEN vendor_count__0 END) as vendor_count, ANY_VALUE(CASE WHEN group_set=0 THEN total_sale_dollars__0 END) as total_sale_dollars, ANY_VALUE(CASE WHEN group_set=0 THEN total_bottles__0 END) as total_bottles, ARRAY_AGG(CASE WHEN group_set=1 THEN STRUCT( purchase_month__1 as purchase_month, total_sale_dollars__1 as total_sale_dollars ) END IGNORE NULLS ORDER BY purchase_month__1 ASC ) as by_month, ARRAY_AGG(CASE WHEN group_set=2 THEN STRUCT( category_class__2 as category_class, total_sale_dollars__2 as total_sale_dollars, item_count__2 as item_count ) END IGNORE NULLS ORDER BY total_sale_dollars__2 desc LIMIT 10) as by_class, ARRAY_AGG(CASE WHEN group_set=3 THEN STRUCT( vendor_name__3 as vendor_name, total_sale_dollars__3 as total_sale_dollars, total_bottles__3 as total_bottles ) END IGNORE NULLS ORDER BY total_sale_dollars__3 desc LIMIT 10) as by_vendor_bar_chart, ARRAY_AGG(CASE WHEN group_set=4 THEN STRUCT( vendor_name__4 as vendor_name, item_description__4 as item_description, total_sale_dollars__4 as total_sale_dollars, total_bottles__4 as total_bottles, avg_price_per_100ml__4 as avg_price_per_100ml ) END IGNORE NULLS ORDER BY total_sale_dollars__4 desc LIMIT 5) as top_sellers_by_revenue, ARRAY_AGG(CASE WHEN group_set=5 THEN STRUCT( vendor_name__5 as vendor_name, item_description__5 as item_description, total_sale_dollars__5 as total_sale_dollars, total_bottles__5 as total_bottles, avg_price_per_100ml__5 as avg_price_per_100ml ) END IGNORE NULLS ORDER BY avg_price_per_100ml__5 desc LIMIT 10) as most_expensive_products, ARRAY_AGG(CASE WHEN group_set=6 THEN STRUCT( vendor_name__6 as vendor_name, total_sale_dollars__6 as total_sale_dollars, by_month__6 as by_month, top_sellers_by_revenue__6 as top_sellers_by_revenue, most_expensive_products__6 as most_expensive_products ) END IGNORE NULLS ORDER BY total_sale_dollars__6 desc LIMIT 10) as by_vendor_dashboard FROM __stage1 ORDER BY 1 desc